Shrec'16 Track: Retrieval of Human Subjects from Depth Sensor Data

Eurographics Workshop on 3D Object Retrieval, EG 3DOR

Volumn 2016-January, Issue , 2016, Pages 41-46

  Giachetti, A ^a   Fornasa, F ^a   Parezzan, F ^a   Saletti, A ^a   Zambaldo, L ^a   Zanini, L ^a,e   Achilles, F ^b,c   Ichim, A E ^d   Tombari, F ^b,d   Navab, N ^b,f   Velasco Forero, S ^g  

^a UNIVERSITY OF VERONA   (Italy)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF MUNICH   (Germany)

^d EPFL   (Switzerland)

^e UNIVERSITY OF BOLOGNA   (Italy)

^f JOHNS HOPKINS UNIVERSITY   (United States)

^g PSL RESEARCH UNIVERSITY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER GRAPHICS;

BODY SHAPES; COLOR INFORMATION; DEPTH SENSORS; HUMAN SUBJECTS; ILLUMINATION CONDITIONS; POINT-CLOUDS; SENSORS DATA; SHAPE ACQUISITION; SHAPE INFORMATION; SINGLE-SHOT;

MUSCULOSKELETAL SYSTEM;

EID: 85017482919     PISSN: 19970463     EISSN: 19970471     Source Type: Conference Proceeding    
DOI: 10.2312/3dor.20161086     Document Type: Conference Paper

References (11)

1. BARBOSA B. I., CRISTANI M., DEL BUE A., BAZZANI L., MURINO V.: Re-identification with rgb-d sensors. In First International Workshop on Re-Identification (October 2012). 1.
2. BERNARDINI F., MITTLEMAN J., RUSHMEIER H., SILVA C., TAUBIN G.: The ball-pivoting algorithm for surface reconstruction. Visualization and Computer Graphics, IEEE Transactions on 5, 4 (1999), 349-359. 2.
3. BASTIONI M., RE S., MISRA S.: Ideas and methods for modeling 3d human figures: the principal algorithms used by makehuman and their implementation in a new approach to parametric modeling. In Proceedings of the 1st Bangalore Annual Compute Conference (2008), ACM, p. 10. 4.
4. CIGNONI P., CALLIERI M., CORSINI M., DELLEPIANE M., GANOVELLI F., RANZUGLIA G.: Meshlab: an open-source mesh processing tool. In Eurographics Italian Chapter Conference (2008), vol. 2008, pp. 129-136. 2.
5. ICHIM A. E., TOMBARI F.: Semantic parametric body shape estimation from noisy depth sequences. Robot. Auton. Syst. 75, PB (Jan. 2016), 539-549. URL: http://dx.doi.org/10.1016/j.robot.2015.09.029, doi:10.1016/j.robot.2015.09. 029. 6.
6. LITMAN R., BRONSTEIN A., BRONSTEIN M., CASTELLANI U.: Supervised learning of bag-of-features shape descriptors using sparse coding. In Computer Graphics Forum (2014), vol. 33, Wiley Online Library, pp. 127-136. 6.
7. MUNARO M., FOSSATI A., BASSO A., MENEGATTI E., VAN GOOL L.: One-shot person re-identification with a consumer depth camera. In Person Re-Identification. Springer, 2014, pp. 161-181. 1.
8. PICKUP D., SUN X., ROSIN P., MARTIN R., ET AL.: Shrec'14 track: Shape retrieval of non-rigid 3d human models. In Proc. 3DOR (2014), vol. 4, pp. 101-110. 1.
9. PIGHIN F., SZELISKI R., SALESIN D. H.: Resynthesizing facial animation through 3d model-based tracking. In Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on (1999), vol. 1, IEEE, pp. 143-150. 4.
10. SHILANE P., MIN P., KAZHDAN M., FUNKHOUSER T.: The princeton shape benchmark. In Shape modeling applications, 2004. Proceedings (2004), IEEE, pp. 167-178. 2.
11. WANG J., MA K., KUMAR SINGH V., HUANG T., CHEN T.: Bodyprint: Pose invariant 3d shape matching of human bodies. In Proceedings of the IEEE International Conference on Computer Vision (2015), pp. 1591-1599. 1.